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DBMS > EsgynDB vs. Spark SQL vs. Trafodion vs. XTDB

System Properties Comparison EsgynDB vs. Spark SQL vs. Trafodion vs. XTDB

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTrafodion  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionSpark SQL is a component on top of 'Spark Core' for structured data processingTransactional SQL-on-Hadoop DBMSA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelRelational DBMSRelational DBMSRelational DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.11
Rank#343  Overall
#46  Document stores
Websitewww.esgyn.cnspark.apache.org/­sqltrafodion.apache.orggithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.htmlwww.xtdb.com/­docs
DeveloperEsgynApache Software FoundationApache Software Foundation, originally developed by HPJuxt Ltd.
Initial release2015201420142019
Current release3.5.0 ( 2.13), September 20232.3.0, February 20191.19, September 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaScalaC++, JavaClojure
Server operating systemsLinuxLinux
OS X
Windows
LinuxAll OS with a Java 8 (and higher) VM
Linux
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes, extensible-data-notation format
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nononono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyeslimited SQL, making use of Apache Calcite
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
ADO.NET
JDBC
ODBC
HTTP REST
JDBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetJava
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.NetClojure
Java
Server-side scripts infoStored proceduresJava Stored ProceduresnoJava Stored Proceduresno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersnoneyes, via HBaseyes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infovia user defined functions and HBaseno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
EsgynDBSpark SQLTrafodionXTDB infoformerly named Crux
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